Senior Cloud Data Specialist

2 weeks ago

Bhavnagar, Gujarat, India beBeeDataEngineer Full time ₹ 10,00,000 - ₹ 15,00,000

We're seeking skilled Data Engineers to design, build and manage robust data pipelines on AWS.

Key Responsibilities:
  • Design, develop and maintain ETL/ELT workflows for structured, unstructured and streaming data in AWS environments.
  • Leverage AWS services such as S3, Glue, EMR, Lambda, Kinesis, Step Functions, Redshift, Athena, DynamoDB, RDS and Lake Formation for scalable data ingestion, transformation, storage and querying.
  • Ensure robust data governance, security and quality controls throughout the data lifecycle, supporting regulatory compliance.
  • Enable both real-time and batch data processing pipelines to power AI-driven workflows and applications.
  • Collaborate closely with AI/ML teams to prepare clean, high-quality datasets optimized for model training, inference and fine-tuning.
  • Optimize data infrastructure to achieve high performance, scalability, reliability and cost efficiency.
  • Implement CI/CD pipelines and data engineering best practices in a cloud-native architecture for automated deployments.
  • Monitor, debug and resolve issues in data pipelines to ensure high availability, reliability and minimal latency.

Required Skills & Qualifications:

  • At least 3 years of hands-on experience in Data Engineering, building data pipelines and cloud-based data solutions.
  • Strong programming skills in Python, SQL and/or Scala/Java.
  • Expertise in AWS cloud services, including S3, Glue, EMR, Redshift, Athena, Kinesis, Lambda, Step Functions, DynamoDB and RDS.
  • Experience with data pipeline orchestration tools such as Apache Airflow, AWS Step Functions, Dagster or similar.
  • Proficiency in big data frameworks like Apache Spark, Hadoop or Flink.
  • Solid understanding of data modeling, data warehousing concepts and schema design principles.
  • In-depth knowledge of data governance, lineage, security policies (IAM roles, encryption, Lake Formation).
  • Hands-on experience in managing real-time streaming data using Kafka, Kinesis or equivalent tools.
  • Familiarity with DevOps practices, including Infrastructure as Code (Terraform, CloudFormation), CI/CD automation, Git and containerization (Docker).

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